An increasing number of cardiac patients undergo diagnostic procedures using different modalities, e.g. Ultrasound (US), Magnetic Resonance Imaging (MRI), Echocardiography (ECG), Electrophysiology (EP), etc. The diagnostic information provided by these procedures is often used to select patients for Implantable Cardiac Defibrillators (ICD).
Identification of candidates for ICD has traditionally been based on the electrophysiologic properties of noninfarcted myocardial tissue and the factors that trigger the induction of lethal arrhythmias in these patients. It has been shown, however, that reentrant Ventricular Tachycardia (VT) commonly originates at the interface or the border zone between myocardial scar tissue and preserved myocardial tissue, which, in turn, may precipitate cardiac arrest in the absence of active ischemia. The mechanical behavior of left ventricular wall segments with different degrees of scar tissue located at different distances from the interface between infarcted and noninfarcted myocardial tissue can help predict inducibility of monomorphic ventricular tachycardia (VT) in patients with ischemic cardiomyopathy. Thus, enhanced border zone mechanical function is a potential marker to VT inducibility in patients with prior myocardial infarction (MI) and left ventricular dysfunction.
Until recently, tagged-MRI was the only modality that provided assessment of myocardial mechanical function. Tagged MRI is, however, not the modality of choice for assessing myocardial mechanical function due to poor resolution. Echo based 2D and 3D speckle tracking allow higher spatial and temporal resolutions at significantly lower costs. Furthermore, once a pacemaker has been implanted further MRI studies (e.g. for following up and future adjustments) are precluded. Ideally, combined visual information would add incremental and significant information about myocardial function.
To date, the tools used for cardiac imaging and diagnostics are limited to post-processing workstations, cardiovascular workstations with one specific modality (such as ultrasound, for example), or CV PACS system, which provides the means to store, access, view, interact and report on the results of CV imaging procedures. Typically, the PACS systems has ‘multi-modality’ capability but limited ‘post-processing’ functionality.
The existing tools today do not provide segmentation solutions for “long-axis” MRI images (only for “short-axis” (closed forms) but with limited accuracy). None of the existing tools provide for automatic processing of left ventricular segmentation, and automatic calculations of clinical indices (LV volume, stroke volume, etc.). None of the existing tools provide for data for longitudinal deformation in MRI “long-axis” images, and thus no ability to calculate strains. Moreover, none of the existing tools allow for fusion of LE-MRI with c-MRI or for fusion of echocardiography and c-MRI or other imaging modalities with one another.
Moreover, while cardiac magnetic resonance (CMR) imaging has emerged as an established technique providing accurate information on myocardial function and myocardial scar, and late gadolinium enhancement (LGE) CMR is used for evaluating perfusion pathologies and for distinguishing between reversible and irreversible myocardial ischemic injury, myocardial deformation imaging allows for objective assessment of myocardial function. The currently applied reference method for analysis of myocardial deformation in CMR is tagged MRI (TMRI). Myocardial tagging refers to a family of techniques that lay out a saturation grid or series of saturation lines across the heart. Deformations of these lines due to myocardial contraction are then monitored and provide an in-plane motion component (2D motion).
Tagging can be used to measure myocardial strain, but quantitative analysis of tagged images is not straightforward. Some disadvantages of tagging are that it requires a specific and unique acquisition protocol, it usually suffers from progressive deterioration of the tag signal during the cardiac cycle, and it requires long breath-hold acquisition and time-consuming post-processing.
Thus, for a routine comprehensive evaluation of myocardial function and viability, other methods are needed.
Others MRI techniques for analysis of regional ventricular function include phase contrast MR imaging (PCMRI), displacement encoding with simulated echoes (DENSE), and strain encoding (SENC) MR. One drawback common to all of these approaches, among others, is that they require acquisition of a specialized image dataset at the time of the examination, typically in addition to the standard cine CMR of the ventricles. Thus, they require a priori planning, increase the duration of the examination, and cannot be applied retrospectively to existing CMR datasets.
There is thus a need for a tool for enhanced measurement of myocardial mechanical function.